From 9fe67cfa52625f3a83dc6f8b2c263618f3351abf Mon Sep 17 00:00:00 2001
From: HuangHai <10402852@qq.com>
Date: Wed, 26 Mar 2025 21:16:14 +0800
Subject: [PATCH] 'commit'

---
 AI/WxMini/Start.py           | 16 ++++++++--------
 AI/WxMini/Utils/MySQLUtil.py |  4 ++--
 2 files changed, 10 insertions(+), 10 deletions(-)

diff --git a/AI/WxMini/Start.py b/AI/WxMini/Start.py
index 372b97fb..dd62f9ba 100644
--- a/AI/WxMini/Start.py
+++ b/AI/WxMini/Start.py
@@ -83,7 +83,7 @@ async def on_session_end(person_id):
         input_word = file.read()
     prompt = (
         "分析用户是否存在心理健康方面的问题:"
-        f"参考分类文档内容如下：{input_word},"
+        f"参考分类文档内容如下：{input_word},注意：只有情节比较严重的才认为有健康问题，轻微的不算。"
         "如果没有健康问题请回复: OK；否则回复：NO，换行后输出问题类型的名称"
         f"\n\n聊天记录：{history}"
     )
@@ -268,7 +268,7 @@ async def reply(person_id: str = Form(...),
                         # 查询非向量字段
                         record = await asyncio.to_thread(collection_manager.query_by_id, hit.id)
                         if record:
-                            logger.info(f"查询到的记录: {record}")
+                            #logger.info(f"查询到的记录: {record}")
                             # 添加历史交互
                             history_prompt += f"用户: {record['user_input']}\n大模型: {record['model_response']}\n"
                     except Exception as e:
@@ -276,7 +276,7 @@ async def reply(person_id: str = Form(...),
 
         # 限制历史交互提示词长度
         history_prompt = history_prompt[:2000]
-        logger.info(f"历史交互提示词: {history_prompt}")
+        #logger.info(f"历史交互提示词: {history_prompt}")
 
         # 调用大模型，将历史交互作为提示词
         try:
@@ -315,7 +315,7 @@ async def reply(person_id: str = Form(...),
             if len(result) > 500:
                 logger.warning(f"大模型回复被截断，原始长度: {len(result)}")
             await asyncio.to_thread(collection_manager.insert_data, entities)
-            logger.info("用户输入和大模型反馈已记录到向量数据库。")
+            #logger.info("用户输入和大模型反馈已记录到向量数据库。")
 
             # 调用 TTS 生成 MP3
             uuid_str = str(uuid.uuid4())
@@ -328,7 +328,7 @@ async def reply(person_id: str = Form(...),
             t = TTS(None)  # 传入 None 表示不保存到本地文件
             audio_data, duration = await asyncio.to_thread(t.generate_audio,
                                                            result)  # 假设 TTS 类有一个 generate_audio 方法返回音频数据
-            print(f"音频时长: {duration} 秒")
+            #print(f"音频时长: {duration} 秒")
 
             # 将音频数据直接上传到 OSS
             await asyncio.to_thread(upload_mp3_to_oss_from_memory, tts_file, audio_data)
@@ -339,7 +339,7 @@ async def reply(person_id: str = Form(...),
 
             # 记录聊天数据到 MySQL
             await save_chat_to_mysql(app.state.mysql_pool, person_id, prompt, result, url, duration)
-            logger.info("用户输入和大模型反馈已记录到 MySQL 数据库。")
+            #logger.info("用户输入和大模型反馈已记录到 MySQL 数据库。")
 
             # 调用会话检查机制
             await on_session_end(person_id)
@@ -368,7 +368,7 @@ async def reply(person_id: str = Form(...),
 @app.get("/aichat/get_chat_log")
 async def get_chat_log(
         person_id: str,
-        page: int = Query(default=1, ge=1, description="当前页码（默认值为 1，但会动态计算为最后一页）"),
+        page: int = Query(default=1, ge=1, description="当前页码"),
         page_size: int = Query(default=10, ge=1, le=100, description="每页记录数"),
         current_user: dict = Depends(get_current_user)
 ):
@@ -387,7 +387,7 @@ async def get_chat_log(
 # 获取风险聊天记录接口
 @app.get("/aichat/get_risk_chat_logs")
 async def get_risk_chat_logs(
-        risk_flag: int = Query(..., description="风险标志（1 表示有风险，0 表示无风险）"),
+        risk_flag: int = Query(..., description="风险标志（1 表示有风险，0 表示无风险 ,2:处理完毕）"),
         page: int = Query(default=1, ge=1, description="当前页码（默认值为 1）"),
         page_size: int = Query(default=10, ge=1, le=100, description="每页记录数（默认值为 10，最大值为 100）"),
         current_user: dict = Depends(get_current_user)
diff --git a/AI/WxMini/Utils/MySQLUtil.py b/AI/WxMini/Utils/MySQLUtil.py
index a7bc1e03..7a123f8b 100644
--- a/AI/WxMini/Utils/MySQLUtil.py
+++ b/AI/WxMini/Utils/MySQLUtil.py
@@ -78,7 +78,7 @@ async def get_chat_log_by_session(mysql_pool, current_user, person_id, page=1, p
 
             # 查询分页数据，按 id 降序排列
             await cur.execute(
-                "SELECT id, person_id, user_input, model_response, audio_url, duration, create_time "
+                "SELECT SQL_NO_CACHE id, person_id, user_input, model_response, audio_url, duration, create_time "
                 "FROM t_chat_log WHERE person_id = %s ORDER BY id DESC LIMIT %s OFFSET %s",
                 (person_id, page_size, offset)
             )
@@ -184,7 +184,7 @@ async def get_chat_logs_by_risk_flag(mysql_pool, risk_flag: int, offset: int, pa
         async with conn.cursor() as cursor:
             # 查询符合条件的记录
             sql = """
-                SELECT 
+                SELECT  SQL_NO_CACHE
                     tcl.id, tcl.user_input, tcl.model_response, tcl.audio_url, tcl.duration, 
                     tcl.create_time, tcl.risk_flag, tcl.risk_memo, tcl.risk_result, 
                     tbp.person_id, tbp.login_name, tbp.person_name